7.1.7.

What are trends in sequential process or product data?

Detecting trends by plotting the data points to see if a line
with an obviously non-zero slope fits the points

Detecting trends is equivalent to comparing the process values to
what we would expect a series of numbers to look like if there were
no trends. If we see a significant departure from a model where
the next observation is equally likely to go up or down, then we
would reject the hypothesis of "no trend".

A common way of investigating for trends is to fit a straight line
to the data and observe the line's direction (or slope). If the
line looks horizontal, then there is no evidence of a trend;
otherwise there is. Formally, this is done by testing whether the
slope of the line is significantly different from zero. The
methodology for this is covered in Chapter
4.

Other trend tests

A non-parametric approach for detecting significant trends known
as the Reverse Arrangement Test is described in Chapter 8.